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Models/AOC-MF (val)

AOC-MF (val)

Reported on 8 benchmarks across 2 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision8 results

  • VideoonDAVIS 2017
    F-Score· 2022-07-02
    85.9
    SOTA
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • VideoonDAVIS 2017
    Jaccard (Mean)· 2022-07-02
    81.7
    SOTA
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • VideoonDAVIS 2016
    F-Score· 2022-07-02
    94.7
    SOTA
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • Video Object SegmentationonDAVIS 2017
    F-Score· 2022-07-02
    85.9
    SOTA
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • Video Object SegmentationonDAVIS 2017
    Jaccard (Mean)· 2022-07-02
    81.7
    SOTA
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • Video Object SegmentationonDAVIS 2016
    F-Score· 2022-07-02
    94.7
    SOTA
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • VideoonDAVIS 2016
    Jaccard (Mean)· 2022-07-02
    88.5
    best: 92.5 (ISVOS (BL30K, MS))
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887
  • Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· 2022-07-02
    88.5
    best: 92.5 (ISVOS (BL30K, MS))
    Towards Robust Video Object Segmentation with Adaptive Object CalibrationarXiv:2207.00887